Description
Machine Learning Applied to Stock & Crypto Trading – Python is the name of the machine learning course applied to stock and cryptocurrency trading with Python, published by Udemy Academy. This course teaches you to excel in financial trading by applying machine learning techniques to financial data using Python. This course does not cover a lot of deep theory. This is a very hands-on course, with high-level theory for anyone who can easily grasp the basic concepts, but more importantly, understand the program and use it immediately. If you are looking for a course with a lot of math, this course is not for you. If you are looking for a course to experience using financial data in a fun, exciting and potentially profitable way, you will probably enjoy this course very much.
What you will learn in the Machine Learning Applied to Stock & Crypto Trading – Python course:
- Understand hidden states and regimes for any market or asset using hidden Markov models
- Discover optimal assets to trade in ETFs, stocks, forex or crypto using K-Means Clustering
- Compress information from a wide set of indicators with PCA
- Make objective future predictions on financial data with XGBOOST
- Train a reinforcement learning AI model for stock trading with PPO
- Determine the market efficiency on each asset
- Learn about Python libraries including pandas, PyTorch (for deep learning), and sklearn.
Course details
Publisher: Yudmi
teacher: Shaun McDonogh
English language
Training level: introductory to advanced
Number of courses: 111
Training duration: 17 hours and 49 minutes
Course headings
Course prerequisites
You should have some basic experience with Python
You should be aware of trading related concepts like Pairs Trading
You should have awareness of assets like ETF’s, the VIX, Stocks and Crypto
Course images
Course introduction video
Instructions for use and tips
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
Changes:
Version 2024/2 compared to 2022/7 has increased the number of 3 lessons and the duration of 25 minutes. English subtitles have also been added to the course.
download link
File(s) password: www.downloadly.ir
Size
8.51 GB
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